Stochastic dynamics of driven Brownian particles in viscoelastic solvents
by Juliana Catharina Caspers
Date of Examination:2024-12-10
Date of issue:2025-01-13
Advisor:Prof. Dr. Matthias Krüger
Referee:Prof. Dr. Matthias Krüger
Referee:Dr. Aljaz Godec
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Abstract
English
Since its seminal discovery by the botanist Robert Brown, Brownian motion has become an important paradigm in statistical physics. It describes the incessant, random motion of small (Brownian) particles suspended in a solvent caused by collisions with solvent molecules. In Newtonian fluids, the stochastic dynamics of a Brownian particle is described by the famous Langevin equation with uncorrelated, zero-mean noise accounting for the random collisions. This description relies on the assumption that the solvent molecules relax much faster than the Brownian particle, so that the solvent remains in equilibrium even as the particle is driven. This assumption is not feasible for viscoelastic solvents, such as blood, cytoplasm, colloidal suspensions, micellar or polymer solutions. These have a complex microstructure that allows for the storage and dissipation of energy, resulting in long relaxation times that are similar to those of the particle motion, as well as pronounced nonlinear properties. Therefore, Brownian particles in viscoelastic solvents experience memory; they remember their past motion, which gives rise to a variety of novel phenomena. In a theoretical description, such non-Markovian behavior can be obtained by integrating or projecting out the solvent degrees of freedom. The description becomes particularly challenging beyond equilibrium, for example when a Brownian particle is driven. The particle excites the solvent out of equilibrium and can be subject to strong nonlinear responses and non-equilibrium fluctuations. Nevertheless, understanding such systems is crucial for many biological and technological applications, such as drug delivery and microfluidic devices. This dissertation is dedicated to the analysis, modeling and understanding of the stochastic dynamics of Brownian particles in viscoelastic solvents under the application of different driving protocols. At the level of coarse-grained dynamics, we will introduce simple bath-particle models that show remarkable agreement with experiments in micellar solutions. By applying a path integral formalism, we will establish a novel theoretical framework to systematically describe the nonlinear response and non-equilibrium fluctuations of the force acting on a driven particle.
Keywords: Statistical Physics; Non-Markovian dynamics; Nonlinear Langevin description; Nonlinear Response Theory; Path integral formalism; Stochastic dynamics; Viscoelastic solvents; Brownian motion; Bath-particle models